A study was conducted at the University of Baghdad-College of Agricultural Engineering Sciences - Department of Agricultural Machinery and Equipment for the agricultural season 2023 with the aim of designing, manufacturing and testing a machine used to planting agricultural nursery tray with different types of vegetable or horticultural seeds or forest seeds of various forms, and using different agricultural media where they are conducted The planting process is by pulling the seeds with a negative pressure vacuum system, and then they are feding to the dishes in their right place to complete the planting process. The study included three factors: The speed of the main belt in three levels: 0.43, 0.66 and 0.90 m.sec−1 and three types of agricultural media: Petmus, mix of Petmos and silt 1:1 and silt, and three types of seeds that were planted. A factorial experiment was carried out using a design (CRD) with three replications using the least significant difference and a probability level (LSD = 0.05) to compare the mean of the coefficients. Some performance indicators of the machine were studied, including: Consumed electrical power, electric power, the productivity of the machine, and the efficiency of the machine in picking seeds. The results indicated The peat moss medium excelled in recording the least consumed electric power, which amounted to 2075.8 watts, and the lowest electric power, which amounted to 0.007751 kWh. And the third speed of the conveyor belt excelled in achieving the highest productivity of dishes per hour, amounting to 105.08 dishes.hour−1, and the first speed achieved the least consumed power, amounting to 2047.3 watts, and the least consumed electrical energy at the third speed, which amounted to 0.007703 kWh.
The aim of this research is to use robust technique by trimming, as the analysis of maximum likelihood (ML) often fails in the case of outliers in the studied phenomenon. Where the (MLE) will lose its advantages because of the bad influence caused by the Outliers. In order to address this problem, new statistical methods have been developed so as not to be affected by the outliers. These methods have robustness or resistance. Therefore, maximum trimmed likelihood: (MTL) is a good alternative to achieve more results. Acceptability and analogies, but weights can be used to increase the efficiency of the resulting capacities and to increase the strength of the estimate using the maximum weighted trimmed likelihood (MWTL). In order to perform t
... Show MoreThe second half of the last century witnessed a great scientific revolution that was able to bring about wide changes in various fields, including the field of physical education, which plays a fundamental role in the process of change for the better, and which knocked all the doors of modern science in various aspects and from this perspective we see that students have different capabilities And interests and motives, which require providing a differentiated education, and this depends on the necessity of knowing each student and on the school’s ability to know appropriate strategies for teaching each student so there is no single way to teach so the research problem comes in experimenting with an educational method that works on
... Show MoreThe aim of the study was to identify the use of the strategies of numbered heads and brainstorming in learning handspring on the Vault table in artistic gymnastics for Men for the third grade students in the collage of Physical Education and Sport Sciences, as well as to identify the best group among the three research groups (number of heads numbered,, brainstorming strategies And the traditional style group) to learn the skill under study. Using the experimental method, the research subject included the third grade students in the collage of Physical Education and Sports Sciences / University of Baghdad, and randomly by lot, 12 students were selected for each of the three research groups. The study consisted of the arithmetic mean
... Show MoreEach project management system aims to complete the project within its identified objectives: budget, time, and quality. It is achieving the project within the defined deadline that required careful scheduling, that be attained early. Due to the nature of unique repetitive construction projects, time contingency and project uncertainty are necessary for accurate scheduling. It should be integrated and flexible to accommodate the changes without adversely affecting the construction project’s total completion time. Repetitive planning and scheduling methods are more effective and essential. However, they need continuous development because of the evolution of execution methods, essent
Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy
... Show MoreAccurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector funct
Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al
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